Machine learning is the field of study where a computer or computers learn to perform classes of tasks using the feedback generated from the experience or data that the machine learning process acquires during computer performance of those tasks. Typically, machine learning includes provide example inputs for training a machine learned model and, once the model has been trained, it can be used in an inference mode to perform the task on a new, previously unseen, input. The example inputs for training an inference are typically referred to as features. Predictions and classifications made by machine learning models are highly dependent on the features of the input provided. Historical data can be valuable for some such processes, but expensive to store and historical metrics (e.g., counts, averages, ratios, etc.) may require large amounts of processing cycles to calculate.